Automated phase-contrast cardiovascular magnetic resonance flow-rate parameters accurately detected left ventricular diastolic dysfunction with a sensitivity >0.83, specificity >0.91, and accuracy >0.89.
Cross-Sectional (n=53)
No
Does automated evaluation of phase-contrast cardiovascular magnetic resonance data accurately assess left ventricular diastolic function compared to Doppler echocardiography in patients with severe aortic valve stenosis?
Automated extraction of diastolic parameters from PC-CMR is reproducible, correlates well with echocardiography, and accurately detects LV diastolic dysfunction.
Absolute Event Rate: 0.54% vs 1.44%
p-value: p=<0.0001
BACKGROUND: Early detection of diastolic dysfunction is crucial for patients with incipient heart failure. Although this evaluation could be performed from phase-contrast (PC) cardiovascular magnetic resonance (CMR) data, its usefulness in clinical routine is not yet established, mainly because the interpretation of such data remains mostly based on manual post-processing. Accordingly, our goal was to develop a robust process to automatically estimate velocity and flow rate-related diastolic parameters from PC-CMR data and to test the consistency of these parameters against echocardiography as well as their ability to characterize left ventricular (LV) diastolic dysfunction. RESULTS: We studied 35 controls and 18 patients with severe aortic valve stenosis and preserved LV ejection fraction who had PC-CMR and Doppler echocardiography exams on the same day. PC-CMR mitral flow and myocardial velocity data were analyzed using custom software for semi-automated extraction of diastolic parameters. Inter-operator reproducibility of flow pattern segmentation and functional parameters was assessed on a sub-group of 30 subjects. The mean percentage of overlap between the transmitral flow segmentations performed by two independent operators was 99.7 ± 1.6%, resulting in a small variability ( 0.71) and receiver operating characteristic (ROC) analysis revealed their ability to separate patients from controls, with sensitivity > 0.80, specificity > 0.80 and accuracy > 0.85. Slight superiority in terms of correlation with echocardiography (r = 0.81) and accuracy to detect LV abnormalities (sensitivity > 0.83, specificity > 0.91 and accuracy > 0.89) was found for the PC-CMR flow-rate related parameters. CONCLUSIONS: A fast and reproducible technique for flow and myocardial PC-CMR data analysis was successfully used on controls and patients to extract consistent velocity-related diastolic parameters, as well as flow rate-related parameters. This technique provides a valuable addition to established CMR tools in the evaluation and the management of patients with diastolic dysfunction.
Bollache et al. (2010) conducted a cross-sectional in Severe aortic valve stenosis with preserved LV ejection fraction (n=53). Automated phase-contrast cardiovascular magnetic resonance (PC-CMR) vs. Doppler echocardiography was evaluated on EfMR/AfMR ratio (flow rate-related parameter) (p=<0.0001). Automated phase-contrast cardiovascular magnetic resonance flow-rate parameters accurately detected left ventricular diastolic dysfunction with a sensitivity >0.83, specificity >0.91, and accuracy >0.89.